import os import openai import gradio as gr openai.api_key = os.environ["OpenAI_Key"] HUGGINGFACE_TOKEN = os.environ["HF_Key"] # huggingface-cli login --token $HUGGINGFACE_TOKEN from transformers import TFGPT2LMHeadModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained('Gracoy/ingredients_compatibility_GPT2_S') model = TFGPT2LMHeadModel.from_pretrained('Gracoy/ingredients_compatibility_GPT2_S') def assistant(assist_prompt): response = openai.ChatCompletion.create( model='gpt-3.5-turbo', messages=assist_prompt, temperature=0.7) return response["choices"][0]["message"]["content"].strip() def proper_ingredient(ingredients, meal): if not ingredients: return assist_prompt1 = [{"role": "user", "content": f"列出三道使用{ingredients}裡食材適合當{meal}的料理，列舉即可不須詳細說明"}] prompt = [ {"role": "system", "content": "你是一個烹飪經驗豐富的廚師，知道哪些食材適合拿來搭配來製作平易近人且美味的料理"}, {"role": "assistant", "content": assistant(assist_prompt1)}, {"role": "user", "content": f"請給我三組在{ingredients}中適合一起烹飪的食材組合，不需要料理名稱只要寫出食材和為何他們適合搭配在一起就好，\ 列出的食材組合需至少包含一樣原本提供的食材，###輸出格式：至少一樣原本食材+新增食材：為何適合搭配在一起###"} ] response = openai.ChatCompletion.create( model='gpt-3.5-turbo', messages=prompt, temperature=0.7) return response["choices"][0]["message"]["content"].strip() def get_ingre(ingredients): final_ingre = ingredients return final_ingre def gen_recipe(final_ingredients, flavor, meal): global step global round global history step = 9 round = 0 history = [] if not final_ingredients: return assist_prompt1 = [{"role": "user", "content": f"請用三句話說明料理中的{flavor}風味，列出{flavor}風味常使用的香料及調味料，列舉即可不須詳細說明"}] assist_prompt2 = [{"role": "user", "content": f"列出三樣以{final_ingredients}裡的食材烹調出適合當{meal}的{flavor}風味料理，列舉即可不須詳細說明"}] prompt = [ {"role": "system", "content": "你是一個烹飪經驗豐富的廚師，擅長使用手邊的食材和簡潔的烹飪步驟來製作平易近人的家庭料理"}, {"role": "assistant", "content": assistant(assist_prompt1)}, {"role": "assistant", "content": assistant(assist_prompt2)}, {"role": "user", "content": f"請在上述料理中選擇一個，並針對此料理給我一份步驟數在{step}步以內的食譜，烹飪方式不要用炒的，食材用量要詳細，\ 食譜要包含用到的調味料，烹飪步驟要簡潔；###使用食材：{final_ingredients}，料理風味：{flavor}，餐點：{meal}\ ###；###輸出格式:料理名稱,使用食材,使用調味料,烹飪步驟,分成三個區塊顯示###"} ] response = openai.ChatCompletion.create( model='gpt-3.5-turbo', messages=prompt, temperature=0.7) round += 1 history.append(response["choices"][0]["message"]["content"].strip()) return response["choices"][0]["message"]["content"].strip() def another_recipe(final_ingredients, flavor, meal): global step global round global history if round == 0 or (not final_ingredients): return step = 9 assist_prompt1 = [{"role": "user", "content": f"請用三句話說明料理中的{flavor}風味，列出{flavor}風味常使用的香料及調味料，列舉即可不須詳細說明"}] assist_prompt2 = [{"role": "user", "content": f"你給我的{history[round-1]}料理名稱與食譜我都不喜歡，\ 請列出其他三樣以{final_ingredients}裡的食材烹調出適合當{meal}的{flavor}風味料理，列舉即可不須詳細說明"}] prompt = [ {"role": "system", "content": "你是一個烹飪經驗豐富的家庭主婦，擅長使用簡潔的烹飪步驟來製作平易近人的料理"}, {"role": "assistant", "content": assistant(assist_prompt1)}, {"role": "assistant", "content": assistant(assist_prompt2)}, {"role": "user", "content": f"請在上述料理中給我一份料理名稱不在{history}裡且步驟數在{step}步以內的食譜，烹飪方式不要用炒的, \ 食材用量要詳細，食譜要包含用到的調味料，烹飪步驟的描述要簡潔；###使用食材：{final_ingredients}，料理風味：{flavor}，餐點：{meal}\ ###；###輸出格式:料理名稱,使用食材,使用調味料,烹飪步驟,分成三個區塊顯示###"} ] response = openai.ChatCompletion.create( model='gpt-3.5-turbo', messages=prompt, temperature=0.5) round += 1 history.append(response["choices"][0]["message"]["content"].strip()) return response["choices"][0]["message"]["content"].strip() def simpler_recipe(final_ingredients, flavor, meal): global step global round global history if round == 0 or (not final_ingredients): return step = step - 2 if step > 5 else step assist_prompt1 = [{"role": "user", "content": f"請用三句話說明料理中的{flavor}風味，列出{flavor}風味常使用的香料及調味料，列舉即可不須詳細說明"}] assist_prompt2 = [{"role": "user", "content": f"你給我的{history[round-1]}食譜做法太難了，請列出其他三樣以{final_ingredients}裡的食材，\ 烹調出適合當{meal}的{flavor}風味料理，列舉即可不須詳細說明"}] prompt = [ {"role": "system", "content": "你是一個烹飪技巧不熟練的新手廚師，只能製作出簡單常見的料理"}, {"role": "assistant", "content": assistant(assist_prompt1)}, {"role": "assistant", "content": assistant(assist_prompt2)}, {"role": "user", "content": f"請給我一份料理名稱不在{history}裡且烹飪步驟在{step}步以內的食譜，先用一句話說明你對{history[round-1]}食譜做了哪些調整，烹飪方式不要用炒的，\ 食材用量要詳細，最多只能使用三種調味料，烹飪步驟要簡潔；###使用食材：{final_ingredients}，料理風味：{flavor}，餐點：{meal}\ ###；###輸出格式:料理名稱,使用食材,使用調味料,烹飪步驟,分成三個區塊顯示###"} ] response = openai.ChatCompletion.create( model='gpt-3.5-turbo', messages=prompt, temperature=0.7) round += 1 history.append(response["choices"][0]["message"]["content"].strip()) return response["choices"][0]["message"]["content"].strip() def compatibility_predict(ingredients): response = openai.ChatCompletion.create( model='gpt-3.5-turbo', messages=[{"role": "user", "content": f"請把以下輸入翻譯成英文:{ingredients}"}] ) translated = response['choices'][0]['message']['content'].strip().lower().replace('.', "") prefix = 'I want to cook, please select the suitable ingredients from the following list: ' prompt = prefix + translated+ '.' input = tokenizer('' + prompt, return_tensors='tf') encoded_outputs = model.generate(input['input_ids'], max_length=128, num_beams=3, num_return_sequences=1, early_stopping=True) mid = 'The best combinations are: ' suffix = '. Enjoy your dish!' res = [] for output in encoded_outputs: ans = tokenizer.decode(output, skip_special_tokens=True) ans = ans.replace(prompt, "").strip() ans = ans.replace(mid, "").strip() ans = ans.replace(suffix, "").strip() ans = set(ans.split(', ')) res.append(list(ans)) response = openai.ChatCompletion.create( model='gpt-3.5-turbo', messages=[{"role": "user", "content": f"請把以下輸入翻譯成繁體中文，翻譯時請以台灣(Taiwan)的習慣用詞為準:{', '.join(ans)}"}] ) return response["choices"][0]["message"]["content"].strip() with gr.Blocks(css="footer{display: none !important;}", theme=gr.themes.Soft(primary_hue="zinc", neutral_hue="sky")) as demo1: gr.Markdown(""" # 今晚我想來點 """) with gr.Row(): with gr.Column(): ingredients = gr.Textbox(label='手邊有哪些其他食材呢？') #meal = gr.Textbox(label='現在要吃的是早餐，午餐，點心，晚餐，還是宵夜？') meal = gr.Radio(["早餐", "午餐", "晚餐", "點心", "宵夜"], label="你現在要烹煮的是哪一餐？") submit_bnt = gr.Button('請推薦食材組合給我') proper_set = gr.Textbox(label='推薦的食材組合') with gr.Column(): final_ingredients = gr.Textbox(label="最後想使用的食材有哪些？", info="預設帶入原本輸入的食材，可再自行增減") flavor = gr.Dropdown(['中式','日式','美式','韓式','義式','泰式','都可以'],label='你希望成品帶有哪些風味？', info="請從選單中任選一個") submit_bnt1 = gr.Button('產生食譜吧！') recipe = gr.Textbox(label='食譜') with gr.Row(): simpler_btn = gr.Button('太難了') another_btn = gr.Button('不喜歡') submit_bnt.click(fn=compatibility_predict, inputs=[ingredients], outputs=[proper_set]) # 這邊把原本的proper_ingredient換成我們model的API, 其他按鈕都沒改 submit_bnt.click(fn=get_ingre, inputs=[ingredients], outputs=[final_ingredients]) submit_bnt1.click(fn=gen_recipe, inputs=[final_ingredients, flavor, meal], outputs=[recipe]) simpler_btn.click(fn=simpler_recipe, inputs=[final_ingredients, flavor, meal], outputs=[recipe]) another_btn.click(fn=another_recipe, inputs=[final_ingredients, flavor, meal], outputs=[recipe]) demo1.launch()